Field
The disclosure relates to the technical field of perspective imaging, in particular, to a method and a system for estimating a point spread function.
Description of Related Information
In a perspective imaging system, an image is likely to be blurry due to movement of a scanning device and crosstalk of detectors, which have impacts on visual effects of the image, observation of the image and finding of suspicious areas from the image by an inspector. Image quality degradation of the system can be approximated as a convolution of a point spread function (PSF) to the image. The image can be deblurred by some image restoration technologies so as to get a clear image if the PSF was known. In addition, the quantitative description of the PSF can be used as an important index evaluating the imaging quality of the system, and a suggestion from deeply analyzing the PSF may be provided to improve software and hardware of the system.
The PSF is required to be estimated to improve image quality and analyze the reasons of image degradation. Most of the existing estimating approaches, such as the typical Cepstrum Approach, the Variational Bayesian Approach, the Sparsity Constrained Optimization Approach, etc., are used for a visible light imaging system. These approaches are used for common images and have poor estimation accuracy without specific devices, and most of them have slow computation speed. Some parameters of a testing device and system, such as width of a slit, radius of a hole, physical size of a detector, etc., should be known accurately for the approaches used in an X-ray imaging system. If the testing device is improperly designed or has low processing precision, an inaccurate estimation and a complex computing process will be occurred readily.